University of Arkansas, Fayetteville
ScholarWorks@UARK
Economics Undergraduate Honors Theses
Economics
5-2012
The Economic Impact of Right-To-Work Laws on
Employment and Living Standards in the State of
Arkansas
Brinkley Cook-campbell
University of Arkansas, Fayetteville
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Recommended Citation
Cook-campbell, Brinkley, "The Economic Impact of Right-To-Work Laws on Employment and Living Standards in the State of
Arkansas" (2012). Economics Undergraduate Honors Theses. 6.
http://scholarworks.uark.edu/econuht/6
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The Economic Impact of Right-To-Work Laws on Employment and Living Standards in
the State of Arkansas
by
Brinkley Beecher Cook-Campbell
Advisor: Dr. Robert Stapp
An Honors Thesis in partial fulfillment of the requirements for the degree Bachelor of
Science in Business Administration in Economics.
Sam M. Walton College of Business
University of Arkansas
Fayetteville, AR
May 11, 2012
1
Table of Contents
Introduction…………………………………………………………………….……….3
Historical Context………………………………………………………………………3
Background Information …………………………………………………………….....5
Review of Past Studies ……………………………………………………...…………6
Descriptive Statistics……………………………………………………………...........6
Methodology ……………………………………………………………….................15
Results………….....……………………………………………………………….….15
Conclusion…………………………………………………………………….………18
Works Cited…………………………………………………………………………..20
2
Introduction
In order for civilized nations such as the United States to enjoy peace and economic
stability, it is essential that the current government have the authority to settle disputes that may
arise between entities that do not enjoy an alignment of values. It is the responsibility of all
levels of government to make rulings that promote civil rights and liberties with an emphasis on
the well-being of the general public. Nowhere is this more evident than in the realm of
competition and misalignment of goals that exists between organized labor and capitalistic
employers. While organized labor’s goals are often concerned with job security, pay increases,
fringe benefits, safety standards, and/or representational rights, employers of all types are more
likely to be concerned with controlling costs and maximizing a business’s bottom line. While in
a perfect world, labor unions and corporations would be willing to work together to achieve
mutual benefits, it is no surprise that their goals often stand in stark contrast to one another.
Historical Context
Labor unions are not a creation of the American capitalistic society. Organized labor
dates as far back as the late fourteenth century in the form of guilds in the Flemish cloth industry
(Munro, 2000). The precursor to modern-day labor unions was a group of all male workers
known as “fullers” and when the Count of Flanders tried to enact policies of wage reduction,
they went on strike. This ultimately led to a labor agreement under which only half of the
originally proposed wage cut was enacted. Collective bargaining was born. Despite their very
primitive origins in the Flemish clothing industry, workers guilds would ultimately develop into
the modern-day labor unions that possess great amounts of bargaining power and political
influence. As democracy began to take hold in some of the World’s largest countries, labor
unions that sought to preserve the safety and financial stability of the individual worker became
increasingly popular. Nowhere did workers banding together for mutual gain play a bigger part
in the economy than in the young American colonies. In his book Labor in America: A History,
Melvin Dubofsky says that the first “trade societies” in America were made up of both skilled
and journeymen workers who performed jobs such as “carpenters and masons, shipwrights, and
sail makers, as well as tanners, weavers, shoemakers, tailors, smiths, coopers, glaziers, and
printers.” These workers had three basic goals: higher wages (or at least the preservation of
current wages), shorter hours, and improved working conditions (Dubofsky, 2004). These early
trade societies sought to attain these goals largely through peaceful demonstrations, particularly
strikes. As time went on, union power and membership underwent a cyclical increase in
influence that tended to trend upward during times of prosperity and downward during more
difficult economic times.
For the majority of U.S. history, the story has been the same. Unions strove to gain
political influence so they might tip the scales of power in their favor, while capitalist
entrepreneurs sought to use their monetary resources to limit the influence that unions could
have. The fact that unions were slowly but surely gaining ground was evident. In 1913, President
Taft signed a bill that made the Department of Labor a cabinet department (Columbia, 2011).
This was evidence of the progress that organized labor was making in America. Due to the large
number of labor disputes that were taking place in the industrial sector, on July 5, 1935,
President Franklin Roosevelt signed the National Labor Relations Act into law (2011). As the
“primary law governing relations between employers and employees in the private sector,” the
3
NLRA established the National Labor Relations Board to handle disputes between the two
parties (2011). The National Labor Relations Act, also known as the Wagner Act, guaranteed the
“rights of labor to organize and bargain collectively through representatives of their own choice”
(Columbia, 2011). Essentially, the Wagner Act protected employees from union busting
activities by employers and established that workers did indeed have a basic right to collectively
bargain. This was a major gain for workers because they had for so long been at the mercy of the
legal system that tended to favor corporate interests over workers’ rights. Critics of the Wagner
Act claimed that it gave too much power to union leaders. There were a large number of bills
that sought to modify the provisions of the Wagner Act that either died in Congress or were
vetoed by the President. It wasn’t until 1947, that a piece of legislation was successfully passed
that significantly modified the statutes set forth in the Wagner Act. In 1947, Congress passed the
Labor-Management Relations Act (Columbia, 2011). More widely known as the Taft-Hartley
Act, the Labor-Management Relations Act included some provisions that swung the pendulum of
power back toward corporate interests, and put a damper on some of the practices that unions
were able to utilize. Due to the fact that national crises (particularly war) tended to force
governmental and corporate organizations to concede to unions’ demands when strikes were
implemented during times of dire need for industrial output, the Taft-Hartley Act gave the
federal government the right to “obtain an 80-day injunction against any strike that it deemed a
peril to national health or safety” (2011). While this indeed may have been a necessary
provision, it is easy to see why union members saw this as an infringement upon their basic
rights. Another provision in the law that drew criticism from union supporters was the fact that
the Taft-Hartley Act outlawed the “closed shop” (2011). The closed shop is a labor term for
when an organization employs only members of the organization’s representing labor union.
This type of setup gave union leaders a lot of power over their members because belonging to a
labor union was a condition of employment in these types of establishments. The Taft-Hartley
Act also limited the “union shop” to only being permitted if a majority of employees voted in
favor of it. The union shop refers to establishments in which employees can be hired regardless
of whether they are union members or not, but they must join a union within a certain amount of
time to keep their jobs (2011). One result of these two provisions in the Taft-Hartley Act has had
a lasting effect on the economy of the United States for the past 65 years. As a result of the TaftHartley Act being passed, there was a push by business leaders and conservative leaning
politicians to pass “Right-To-Work” laws on a state to state basis. These laws prohibit requiring
an employee to join a union at anytime during their employment, essentially outlawing the union
shop. In addition to outlawing the union shop, RTW laws also outlawed the “agency shop.” The
agency shop referred to some establishments that did not require union membership as a
condition of employment, but did require employees to pay the standard union membership dues.
According to the National Right-To-Work Legal Defense Foundation’s website, twenty-three
states have now passed some form of right-to-work legislation (2012). The proponents of these
laws believe that individuals should have the right-to-work without being forced to become a
member of an organization whose beliefs and values may not be aligned with those of the
individual worker. Opponents of these amendments contend that RTW laws undermine the
ability of workers to organize for collective bargaining and allow for individuals to become
freeloaders, receiving benefits that unions have fought for without paying dues. People who are
in favor of RTW laws contend that these laws are friendly to business, allow business owners to
operate freely without giving an inordinate amount of power to union bosses, and ultimately
promote higher levels of employment in those states. Opponents of these laws disagree with
4
these points, contending that workers in right to work states suffer lower standards of living,
weaker union representation, and lower wages than workers in other states. The purpose of this
research is to look at statistics and the actual effect of right-to-work laws when put into practice
in order to determine if workers and businesses in Arkansas are indeed better off as a result of
Arkansas becoming a right-to-work state.
Background Information
With the passage of Taft-Hartley, states gained the ability to amend their constitutions to
outlaw the union shop and the agency shop if they so chose. Chart 1 shows when the respective
right-to-work states enacted their various laws. The most recent of these states to go RTW is
Indiana, which enacted its constitutional amendment on February 1st, 2012 (Davey, 2012). Figure
1 is a map of the RTW states.
Chart 1: Right-To-Work States by Year of Adoption
State
Florida
Nebraska
Arkansas
Georgia
Iowa
North Carolina
South Dakota
Tennessee
Virginia
Arizona
North Dakota
Nevada
Year of RTW Passage
1943
1947
1947
1947
1947
1947
1947
1947
1947
1947
1948
1951
State
Alabama
South Carolina
Utah
Kansas
Mississippi
Wyoming
Louisiana
Idaho
Texas
Oklahoma
Indiana
Year of RTW Passage
1953
1954
1955
1958
1960
1963
1976
1986
1993
2001
2012
Figure 1: Right-To-Work State Map
5
Review of Past Studies
While opponents and supporters may be set in their opinions as to whether or not RTW
laws are a good thing, previous studies are conflicting at best. Richard Vedder (2010) attributes
increases in population growth, as well as annual growth in average wage rates to right-to-work
laws, citing union monopolies for keeping the marginal labor cost above marginal revenue for
employers. He asserts that this imbalance is more easily dissolved in right-to-work states as a
result of less union power. However, Lonnie Stevans, (2009) contends that while right-to-work
states have a higher number of businesses and self-employment, capital formation, employment
and personal income are either not-statistically different, or lower (in the case of personal
income) in right-to-work states . His study determined that while proprietors’ income is higher in
right-to-work states, “there appears to be little “trickle-down” to the largely non-unionized
workforce in these states”. He also notes that bankruptcies are more common in right-to-work
states than in non-right-to-work states. Lawrence Mishel of the Economic Policy Institute did a
study in 2001 on right-to-work laws and wages that partially controlled for cost of living
differences between states. He found that when controlling for a variety of factors, workers in
right-to-work states earned a statistically significant 3.8% less than their non-right-to-work
counterparts (Mishel, 2001). Emin Dinlersoz and Ruben Hernandez-Murillo (2002) did a study
on manufacturing growth in Idaho before and after its passage of right-to-work laws and while
they did determine that decreased unionization led to an increase in manufacturing growth, it was
inconclusive whether or not they could attribute the decreases in union membership to right-towork laws. One particularly interesting study was done by Robert Krol and Shirley Svorny
(2007). Their paper Unions and Employment Growth: Evidence from State Economic Recoveries
concluded that stronger unions due in part to a lack of right-to-work laws in some states
negatively affected states’ ability to increase employment after periods of economic recession
(2007).
Descriptive Statistics
This paper will look at the impact that right-to-work laws have had on certain economic
statistics that are viewed as major economic indicators. These economic indicators are a good
indication of the current state of the economy. Time series data for these statistics will provide
reviewers with a look at how right-to-work states have fared versus non-right-to-work states over
the past decades. The economic indicators that will be taken into account are the unemployment
rate, the labor force participation rate, population growth rates, and average wage rate growth.
The chief criticism that proponents of unions make of right-to-work legislation is that
laws outlawing the closed shop reduce a union’s ability to retain membership and add new
membership. As a precursor to addressing whether or not right-to-work laws have a significant
effect on the economic performance of states, one must first determine whether or not states with
right-to-work laws actually do have lower rates of union membership. If this is not the case, then
the arguments about whether or not right-to-work laws have a negative impact on union
membership, thereby affecting a state’s economy, are questionable at best.
When taking union participation rates from the Bureau of Economic Analysis and the
Bureau of Labor Statistics and analyzing this data with SAS Enterprise Guide software, it
quickly becomes clear that right-to-work states have much lower union membership than states
without right-to-work laws. As you can see in Chart 2, during the period from 1989 to 2010 the
6
percentage of workers who were union members was always higher on average in states without
right-to-work laws. The differences in these two means were statistically significant for every
year observed. This is also true for the proportion of employee’s who have union representation
as seen in Chart 3. These employees may or may not be members of their place of employment’s
union, but they pay dues and receive union representation just the same as regular members.
These means are also significantly higher in non-right-to-work states.
Chart 2: Union Membership
(Non-RTW, RTW, and Arkansas)
Year
1989
1990
1991
1992
1993
**1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Non-RTW (%)
18.06
17.81
17.88
17.4
17.18
17.2
16.75
16.18
16.14
16.14
15.6
15.6
15.53
15.29
14.78
14.99
14.57
14.57
15.03
14.9
14.26
*99% Confidence Level
RTW (%)
10.17
9.83
9.79
9.71
9.51
8.74
8.5
8.07
7.93
8.19
7.7
7.72
7.38
6.85
6.7
6.5
6.61
6.67
6.68
6.65
6.52
Equality of
Variance
0.0258
0.011
0.0106
0.0156
0.0086
0.2143
0.2168
0.0741
0.0266
0.4298
0.0742
0.0638
0.0042
0.0052
0.0021
0.008
0.014
0.0162
0.0482
0.0209
0.0383
T-Calc
6.3
6.62
6.71
6.32
6.34
6.91
6.96
6.64
7.79
7.15
7.2
7.78
7.34
8.64
8.28
8.14
7.91
7.73
7.94
7.75
7.65
Significance
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
** Data was not available for 1994
7
Sig Diff?
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Arkansas
(%)
9.7
10.3
10.2
8.6
8.3
7.8
7.1
5.9
6.2
7.5
5.8
6.5
5.9
4.8
4.8
4.8
5.1
5.4
5.9
4.2
4
Chart 3: Union Representation
(Non-RTW, RTW, and Arkansas)
Year
1989
1990
1991
1992
1993
**1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Non-RTW
Rep (%)
20.09
20.03
19.9
19.41
19.09
18.97
18.35
17.81
17.55
17.64
17.15
17.13
16.84
16.65
16.08
16.23
15.82
15.93
16.53
16.37
15.58
RTW Rep (%)
12.67
12.33
12.3
12.05
11.87
10.77
10.51
9.89
9.68
9.75
9.37
9.32
8.95
8.41
8.22
7.96
7.94
8.05
8.12
8.04
8.02
* 99% Confidence Level
Equality of
Variance
0.1203
0.071
0.0661
0.0681
0.0311
0.5432
0.6287
0.4535
0.0946
0.508
0.1921
0.1043
0.0165
0.031
0.0117
0.027
0.0849
0.1046
0.1411
0.0765
0.0876
T-Calc
5.22
5.39
5.42
5.28
5.71
6.62
6.37
6.17
6.78
6.83
7.04
7.42
7.49
8.24
7.94
7.88
7.22
7.35
7.87
7.48
6.88
Significance
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
Sig Diff
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Yes*
Arkansas
Rep (%)
12.1
12.1
12.5
11
10.4
9.7
8.4
6.8
7.3
8.6
6.8
8.1
6.7
5.9
6.2
6
6
6.5
7.3
5
5.4
** Data was not available for 1994
It is worth noting that the two states that adopted right-to-work laws during the time period from
1989 to 2010 (Texas in 1993 and Oklahoma in 2001) did not experience drastically lower rates
of union membership in the following years. Both states have experienced falling union
membership rates as the years have gone on, but this trend of decreasing union membership is
not unique to these states. As you can see in Graph 1 below, falling unionization rates is a trend
that is shared by right-to-work states and non-right-to-work states alike. This has been going on
since union membership peaked in 1954 at 35% of the nonagricultural employment (Dubofsky,
2010). It is hard to infer from the data whether or not right-to-work legislation lowers union
participation or if states that have low union participation have values or prevailing ideologies
that make them more likely to pass right-to-work laws. There is a bit of the chicken and the egg
effect that is going on here that makes establishing causality difficult, but we can unequivocally
say that right-to-work states have lower unionization rates than their counterparts.
8
Graph 1 Union Membership and Representation Rates
(Non-RTW, RTW, and Arkansas)
25
Non-RTW Union
Membership
20
RTW Union
Membership
15
Arkansas Union
Membership
10
Non-RTW Represented
RTW - Represented
5
Arkansas Represented
0
Easily one of the most scrutinized and talked about economic statistics is the
unemployment rate. The unemployment rate, in short, measures the percentage of the labor force
participants that are unable to find jobs. More specifically, the unemployment rate is the
percentage of unemployed workers divided by the total number of workers in the labor force.
According to the Bureau of Labor Statistics, the labor force consists of workers who are noninstitutionalized, over the age of sixteen, and are currently employed or if unemployed, have
actively looked for work in the past four weeks. Not surprisingly, this statistic spends a large
amount of time in the spotlight as politicians, policy makers such as the federal reserve board of
governors, organized labor leaders, and employers offer their advice as to how to minimize the
unemployment rate and shield workers from the negative effects of the business cycle.
Individuals who are in favor of right-to-work laws will contend that the increased
influence that unions are privy to in non-right to work states result in wage floors (in the form of
legislated minimum wages, union contracts, etc.) that create a mismatch between the supply of
and the demand for labor. They would contend that unemployment in non right to work states
could be partially attributed to those states’ labor laws. Richard Vedder of the Cato Institute for
Economic Analysis, contends that his statistical analyses have been able to attribute lower
unemployment rates to right-to-work legislation. He points out in his article Right-To-Work
Laws: Liberty, Prosperity, and Quality of Life that in 2007, right to work states had an average
unemployment rate of 4.04%, while non-right-to-work states averaged 4.58% unemployment.
These arithmetic means are good descriptive statistics for an overview of current conditions in
right-to-work states and non-right-to-work states, however more work needs to be done to this
data to determine if these differences are indeed statistically significant and if so, whether or not
they can be attributed to differences in labor laws.
When using SAS Enterprise Guide, a data mining program, to analyze the difference in
means between unemployment data obtained from the Bureau of Labor Statistics, it can be
determined that Right-To-Work States do typically enjoy lower unemployment rates than their
9
non-right-to-work counterparts. However, using the ANOVA t-test for mean function of SAS
produces results that are inconclusive to say the least. As evidenced by Table 3, right-to-work
states had lower unemployment rates than their non-RTW counterparts from 1976 to 1985 and
from 1990 to 2011. Right-to-work states had higher unemployment rates from 1986 to 1989.
However, the differences in average unemployment rates were not statistically different for every
year from 1976 to 2011. Right-to-work states had statistically lower unemployment during the
time periods of 1976 to 1980 and from 1991 to 1996 evaluated at the 95% confidence level. If
confidence standards are relaxed, we can be 90% sure that right-to-work states had lower
unemployment during the years 1981, 1997, 2003, 2006, and 2008. The inconclusive part of this
statistical analysis is that from 1982 to 1990, 1998 to 2002, 2004 to 2005, 2007 and 2009 to 2011
the unemployment rates of right-to-work states and non-right-to-work states had no statistical
difference in their means.
The focal point of this paper is the effect of right-to-work laws on the economy of the
state of Arkansas. The statistical results mentioned in the previous paragraph indicate at least on
the surface that right-to-work laws indeed have a positive effect on individual states’ efforts to
minimize unemployment. However, for Arkansas the results are not as positive. During the time
period of 1976 to 2008 Arkansas averaged a higher unemployment rate than both right-to-work
states and non-right-to-work states in general with the exception of 1993 when Arkansas’s
unemployment was lower than the mean unemployment rate in states without right-to-work laws.
These results are easily seen if you will take a look at Graph 2 below and Chart 4 on the next
page. On the positive side, it is worth noting that Arkansas’s unemployment rate actually fell
below national unemployment rates for both non-right-to-work states and right-to-work states
during the economic downturn during 2009 and 2010. This information is consistent with the
findings of Robert Krol and Shirley Svorny whose economic analysis of unions and their effects
on economic growth concluded that “union influence is linked to slower job growth during
economic recoveries” (2007). Arkansas continued to have a relatively low unemployment rate in
2011 despite the poor national economy, with an 8% unemployment rate versus 8.32%
unemployment in non-right-to-work states and 7.97% unemployment across all right-to-work
states. This appears to bode well for Arkansas’s economic outlook in the foreseeable future.
Graph 2: Unemployment Rate by State
10
9
8
7
Non-RTW
RTW
6
Arkansas
5
4
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
3
10
Chart 4: Unemployment Rates
(Non-RTW, RTW, Arkansas)
Non-RTW RTW
Year (%)
(%)
Equality of Variance T-Calc
Significance
1976
7.67
6.11
0.2534
3.04
0.0038
1977
7.02
5.85
0.3932
2.73
0.0087
1978
6.04
4.98
0.9232
2.73
0.0089
1979
5.88
4.82
0.9713
2.95
0.0049
1980
7.24
6.11
0.2579
2.62
0.0118
1981
7.62
6.69
0.8532
1.8
0.0785
1982
9.45
8.74
1
1.08
0.2857
1983
9.38
8.8
0.7177
0.82
0.4172
1984
7.49
6.93
0.6123
0.9
0.3742
1985
7.06
7.05
0.6441
0.03
0.9796
1986
6.8
7.12
0.9307
-0.49
0.6254
1987
6.02
6.45
0.7588
-0.72
0.4775
1988
5.29
5.7
0.6936
-0.77
0.4443
1989
5.1
5.19
0.9749
-0.23
0.8228
1990
5.62
5.09
0.743
1.63
0.11
1991
6.88
5.72
0.8493
2.86
0.0062
1992
7.33
6.12
0.9653
2.82
0.0069
1993
6.72
5.64
0.8264
2.74
0.0086
1994
5.9
5.17
0.9672
2.07
0.0433
1995
5.51
4.8
0.5563
2.1
0.0405
1996
5.42
4.74
0.3859
2.06
0.0446
1997
4.99
4.33
0.2563
1.99
0.0524
1998
4.57
4.07
0.1184
1.57
0.1238
1999
4.23
3.93
0.0946
1.04
0.3033
2000
3.95
3.79
0.2926
0.63
0.5318
2001
4.6
4.37
0.8114
0.91
0.3656
2002
5.49
5.17
0.9549
1.11
0.2723
2003
5.81
5.31
0.5201
1.69
0.0972
2004
5.37
4.93
0.3142
1.53
0.1332
2005
5.02
4.76
0.4453
0.87
0.3903
2006
4.66
4.14
0.4295
1.81
0.0762
2007
4.6
4
0.7687
2.2
0.0323
2008
5.61
4.96
0.255
1.86
0.0683
2009
8.77
8.08
0.1844
1.25
0.2174
2010
8.99
8.44
0.0514
0.97
0.3384
2011
8.32
7.97
0.0219
0.58
0.5647
* Not Statistically Significant at 95% Confidence Level, but Statistically Significant at 90% Confidence Level
11
Sig Diff?
Yes
Yes
Yes
Yes
Yes
No*
No
No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
No*
No
No
No
No
No
No*
No
No
No*
Yes
No*
No
No
No
Arkansas
(%)
6.8
6.4
6.2
6.1
7.4
8.5
9.3
9.8
8.3
8.5
8.5
8.1
7.7
7
6.8
7.2
7.1
6.1
5.3
4.8
5.1
5.1
5
4.5
4.2
4.7
5.3
5.8
5.6
5.1
5.3
5.3
5.4
7.5
7.9
8
While the unemployment rate is a useful statistic for getting a general idea of the state of
an area’s economy, it is important to keep in mind that it is not the “be-all end-all” statistic that
many in the public tend to make of it. The unemployment rate is most informative when taken in
conjunction with the labor force participation rate. The labor force participation rate is a
measurement of the total number of individuals who are in the labor force (both employed and
unemployed) divided by the total number of the given area’s citizens who are over sixteen and
non-institutionalized. The reason the labor force participation rate is so important is because the
unemployment rate is at its core, a flawed statistic. The unemployment rate is flawed because it
fails to take into account individuals who have been unsuccessful in finding work and have given
up searching for a job. These “discouraged workers” are not technically “unemployed”, but they
are certainly casualties of a less than optimal economy. In order to reinforce or weaken the above
conclusions that right-to-work states have statistically equal unemployment rates as non-right-towork states, and may in fact have lower unemployment rates, labor force participation must be
considered. Based on data from the Bureau of Labor Statistics, SAS statistical analysis reveals
that during the time periods 1976 to 2011, right to work states and their counterparts had
statistically equal labor force participation. From 1976 to 1993, non-right-to-work states had
higher labor force participation, but as previously stated, the differences in averages was not
statistically significant. However, since 1994 right-to-work states have had higher labor force
participation. It is worth noting that in 1993, Texas passed right-to-work legislation. This may
account for the turning point where right-to-work states began to have higher average labor force
participation. This can be observed in Graph 4 below. Much like it did with respect to the
unemployment rate, Arkansas does not fare as well as much of the nation. During the past 35
years, Arkansas has consistently had lower labor force participation than both the right-to-work
states and states without right-to-work laws. As you can see in Graph 3 and Chart 5, Arkansas’s
labor force participation has been approximately 4-5% below the national average during this
time period, following the national trend with startling parallelism, but at a significantly lower
rate.
Graph 3: Labor Force Participation Rate
70
68
66
64
62
Non-RTW (%)
60
RTW (%)
58
Arkansas
56
54
52
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
50
12
Chart 5: Labor Force Participation Rate
(Non-RTW, RTW, Arkansas)
Equality of
Year Non-RTW (%) RTW (%)
Variance
T-Calc Significance Sig Diff?
1976
62.72
62.29
0.3213
0.4
0.689 No
1977
63.31
63.15
0.383
0.14
0.8858 No
1978
64.1
63.62
0.4672
0.46
0.6502 No
1979
64.69
63.94
0.3402
0.7
0.4846 No
1980
64.86
64.14
0.3272
0.67
0.507 No
1981
64.91
64.39
0.5487
0.46
0.6454 No
1982
65.03
64.55
0.7647
0.42
0.6763 No
1983
65.14
64.53
0.8484
0.55
0.5854 No
1984
65.58
64.87
0.7884
0.62
0.5394 No
1985
65.9
65.47
0.7593
0.38
0.7073 No
1986
66.26
66.04
0.4217
0.2
0.8445 No
1987
66.58
66.18
0.424
0.35
0.7252 No
1988
66.83
66.31
0.4423
0.47
0.6427 No
1989
67.37
66.69
0.5086
0.6
0.5501 No
1990
67.66
66.97
0.6255
0.65
0.5161 No
1991
67.4
66.79
0.6618
0.57
0.572 No
1992
67.55
67.05
0.6414
0.47
0.644 No
1993
67.42
67.14
0.9272
0.25
0.807 No
1994
67.52
68.01
0.6465 -0.43
0.6706 No
1995
67.5
68.08
0.5717
-0.5
0.617 No
1996
67.62
67.97
0.5764 -0.31
0.76 No
1997
67.93
67.9
0.6735
0.03
0.9792 No
1998
67.98
67.92
0.8705
0.06
0.9548 No
1999
65.11
65.25
1 -0.12
0.9047 No
2000
65.42
65.37
0.6624
0.05
0.9593 No
2001
64.81
64.53
0.507
0.25
0.8041 No
2002
63.66
63.64
0.3837
0.01
0.9902 No
2003
63.27
63.49
0.513 -0.19
0.8528 No
2004
63.22
63.67
0.4024
-0.4
0.688 No
2005
63.62
63.95
0.3424 -0.31
0.7608 No
2006
64.02
64.41
0.2462 -0.35
0.728 No
2007
63.87
64.5
0.0715 -0.56
0.5787 No
2008
63.16
63.81
0.0268 -0.56
0.5787 No
2009
60.49
60.75
0.0341 -0.19
0.8492 No
2010
59.7
59.8
0.1238 -0.08
0.9364 No
2011
59.7
59.86
0.108 -0.12
0.9056 No
13
Arkansas (%)
57.7
58.6
58.7
59.5
59.5
60.6
60.2
59.8
60.1
60.3
60.8
61.5
62.1
62.8
63.2
62.3
63.0
63.2
64.3
64.3
64.2
63.3
62.9
60
59.8
58.2
59
57.3
58.5
61
60.1
59.7
59.7
57.4
55.3
55.3
Population growth is another important statistic that must be factored into any analysis of
an area’s economic well-being. During the last 30 years, the population of the United States as a
whole has increased from 226,545,805 to 308,745,538, an increase of 36.3%. During that same
time period, Arkansas’s population has grown from 2,286,435 to 2,915,918 or an increase of
27.5%. While Arkansas has not kept up with the nation’s average population growth, it has fared
better than many of its counterparts, some of whom have even had decades in which they
experienced negative population growth. This is important for a state’s economy because as a
population ages, in order to maintain standards of living and steady economic growth, there must
be a younger generation entering the work force to continue the trend of economic growth
increasing output and tax revenue.
In his paper, Right-To-Work Laws: Liberty, Prosperity, and Quality of Life, Richard
Vedder maintains that population growth in right-to-work states has outpaced growth in nonright-to-work states because right-to-work states “allow greater personal liberty with respect to
employment” (2010). Whether this is the case or not remains to be seen. Census data coupled
with statistical analysis using SAS reveals that right-to-work states have indeed outpaced their
counterparts in terms of growth rate. However, the first decade of our analysis did not provide
significant indications that right-to-work laws were having a positive effect on population
growth. During the interval between 1980 and 1990, right-to-work states experienced an average
growth of 10.6% compared to growth of 8.16% among states without right-to-work legislation.
However, this difference was not statistically significant. During that same time period, Arkansas
experienced growth of a mere 2.8%. The 1980-1990 decade did little to cast right-to-work laws
and particularly, Arkansas’s decision to pass them, in a positive light. However the following
two decades were drastically different. As population growth increased across the nation, nonright-to-work states grew at a rate of 10.04%. While this was impressive compared to the
previous decade, right-to-work states far surpassed their counterparts by growing at a rate of
18.34% through this ten year stretch. Furthermore, this difference was statistically significant at
the 98% confidence level. Not only that, but Arkansas grew faster than the average non-right-towork states, with a 13.7% growth rate. The 1990s were very kind to right-to-work states in
general, and while Arkansas did not keep up with the average in that category, it grew at a higher
rate than the non-right-to-work states did. The first decade of the 21st century proved to be more
of the same. Non-right-to-work states grew at a rate of 7.03% but were once again outpaced by
the states with right-to-work laws, which grew by 13.36% on average during the decade. This
difference was also statistically significant at the 99% level. Arkansas experienced respectable
growth of 9.1%, once again growing faster than the average state without right-to-work laws.
The analysis results described above are summarized in Chart 6 below.
Chart 6: Population Growth Rates
(Non-RTW, RTW, Arkansas)
Time
Period
80-90
90-00
00-10
Non-RTW
8.16
10.04
7.03
RTW
10.6
18.34
13.36
Equality of
Variance
0.0358
0.0003
0.0044
T-Calc
-0.67
-2.4
-3.18
* 95% Confidence
14
Significance
0.5069
0.0236
0.0033
Sig Diff?
No
Yes*
Yes*
Arkansas
2.8
13.7
9.1
Methodology
Another question is whether or not this establishes right-to-work laws as a factor of
causation that has a positive effect on population growth. When analyzing Census Department
data with SAS, the results indicate that right-to-work laws have indeed had a positive effect on
population growth during the past two decades. Simple regression however, can be improved
upon. The most glaring trait that one notices when looking at the map of right-to-work states on
page 5 is that most right-to-work states are in the South and West portions of the country, with a
glaring lack of right-to-work states in the Northeastern United States. As Vedder notes in his
analysis, “many of the right-to-work states are located in the Sun Belt, and, other things equal,
many Americans prefer sunny warm climates to cold, damp ones” (2010). U.S. migration and
population patterns show that there has been a trend of people moving further south and west in
recent history. To account for this when doing SAS analysis, the growth rates of states were
matched up with a dummy variable with a value of 1 indicating that a state is one of the 25
southern-most states and a value of 0 indicating a state from the northern half of the country.
This coding was determined by grouping the states by how far south they were in terms of
average latitudinal coordinates. It was expected that the variable for southern states and right-towork laws would be highly correlated, but this was not the case, with a correlation coefficient of
approximately of 0.4. It is also worth noting that in the regression models where population
growth during the 1980s, 1990s, and 2000s respectively, are the dependent variables, states that
adopted right-to-work laws during that time (Idaho, 1986: Texas, 1993: Oklahoma 2001) were
omitted from the analysis during the decade in which they adopted these laws. This is in keeping
with what Lonnie Stevans did in his study of right-to-work laws in 2009.
Results
Regression models using Census data reveal that right-to-work laws did not have a
significant effect on population growth from 1980 to 1990. The model’s R2 in Chart 7 indicates it
is a pretty good fit, explaining roughly 59% of the variation in population growth. The regression
results indicate that instead of right-to-work laws, a better predictor of population growth would
simply be the state’s relative geographical location. Relative geographic location had a
significant, positive effect on population growth in the 80s. On average, the twenty-five
southern-most states experienced a population increase of 7.7% greater than that of the 25
northern most states over this 10 year period with a standard error of the coefficient estimate of
2.565. As one might expect, other large drivers of population growth were the increase in GDP,
the average unemployment rate, and the average labor force participation rate from 1980 to 1990.
All of these variables had a statistically significant effect on population growth and surprisingly,
none of the independent variables in this study were highly correlated with one another. The
independent variable with the largest impact on population growth after the variable denoting
geographic sector was the average unemployment rate variable. Not only was this variable
significant, but surprisingly the sign for the coefficient was a positive 2.8 with a standard error of
.94. This indicates that for every 1% higher the average unemployment rate in a state was during
that time period, the population growth was 2.8% higher average This is a surprising result
indeed, but it may be explained by frictional unemployment. This is a type of unemployment that
is caused by individuals leaving their jobs because they want to look for another one or they are
moving to another area. It makes logical sense that states experiencing higher growth rates would
15
be experiencing higher rates of frictional unemployment. Other significant drivers of population
growth include the average labor force participation rate with a regression coefficient of 1.77 and
a corresponding standard error of 0.38446. This makes sense because individuals moving from
state to state would be more likely to move to states with an abundance of jobs. The same is true
for couples deciding to have children. The more people that an area can manage to keep
employed, the more likely couples are to decide to have children, further contributing to the
population growth. Unfortunately, while the variable denoting right-to-work states has a positive
coefficient, it is not statistically significant at any substantial confidence level. Unfortunately for
the state of Arkansas, while this model would predict Arkansas’s population to have grown by
6.56% during this decade, Arkansas’s population actually grew by only 2.8%. However, if one
has the mindset that since population growth in Arkansas was less than one might expect and
therefore the economic gains that the state experienced can be distributed among a smaller
number of Arkansans, then these results do indeed seem positive. This regression analysis leads
the researcher to conclude that right-to-work laws were not a significant driver of population
growth in the 1980s and that Arkansas may have actually benefitted because of that.
Chart 7: Regression Analysis Population Growth 1980-1990
(Dependent Variable: Pop. Growth)
Source
Model
Error
Corrected Total
Analysis of Variance
Sum of
DF
Squares
5
3903.242
44
2735.13
49
6638.372
Root MSE
7.88429
Dependent Mean
9.166
Coeff Var
86.01671
Mean
Square
780.6484
62.16205
R-Square
Adj R-Sq
F Value
12.56
Pr > F
<.0001
0.588
0.5412
Parameter Estimates
Variable
Intercept
RTW (1) 80-90
South 25
Increase in GDP 80-90
AVG Unemployment 80-90
AVG LFPR 80-90
Parameter
Estimate
-151.463
1.93556
7.73335
0.19205
2.81733
1.77248
DF
1
1
1
1
1
1
Standard
Error
30.3601
2.56502
2.64899
0.03869
0.94165
0.38446
t Value
-4.99
0.75
2.92
4.96
2.99
4.61
Pr > |t|
<.0001
0.4545
0.0055
<.0001
0.0045
<.0001
Alternatively, regression analysis reveals a different picture during the decade of the
1990s. Based on the results of the regression for population growth during the 90s, this research
can conclude that right-to-work laws did have a significant effect on population growth during
this time period. This model explained 75% of the variation in population growth among states
during the 90s as indicated by the R2 of the model. Right-to-work states, on average experienced
a 4.9% greater increase in population that their counter parts did during this decade. Similarly,
southern states grew on average by 5.7% more during the decade than northern states did when
16
other variables are taken into account. The standard errors for these two estimates are 2.077 and
2.155 respectively. States experienced a .31% greater population growth on average for each 1%
increase in GDP over this time period. As in the model for the 1980s population growth, the
average unemployment rate once again had a positive, significant impact on population growth,
this time with a 4.89 coefficient and a standard error of 1.2. As in the previous model, this is
probably attributable to frictional unemployment in high-growth states. The average labor force
participation variable was also significant, with a parameter estimate of 1.35 and a standard error
of .358. This indicates that for each 1% increase in the average labor force participation rate
during the timer period, a state would be predicted to have a 1.35% higher population increase on
average with all other variables held constant. All parameter estimates can be observed in Chart
8 below. This model would have predicted a population growth of 15.4% over the decade for
Arkansas however Arkansas only experienced a population growth of 13.7%. The results of this
model lead the researcher to conclude that right-to-work laws were indeed a significant factor in
population growth during the 90s and while Arkansas grew less than expected, that may not be a
bad thing when the increase in GDP was spread across the state’s economy.
Chart 8: Regression Analysis Population Growth 1990-2000
(Dependent Variable: Pop. Growth)
Source
Model
Error
Corrected Total
Variable
Intercept
RTW (1) 90-00
South 25
Increase in GDP 90-00
AVG Unemployment 90-00
AVG LFPR 90-00
Analysis of Variance
Sum of
DF
Squares
5
4888.177
44
1628.871
49
6517.049
Root MSE
6.08439
Dependent Mean
13.268
Coeff Var
45.85763
Parameter Estimates
Parameter
Estimate
-131.352
4.90205
5.7173
0.31509
4.89073
1.35136
DF
1
1
1
1
1
1
Mean
Square
977.6355
37.0198
R-Square
Adj R-Sq
Standard
Error
29.18703
2.07751
2.15564
0.0376
1.20675
0.3581
F Value
26.41
Pr > F
<.0001
0.7501
0.7217
t Value
-4.5
2.36
2.65
8.38
4.05
3.77
Pr > |t|
<.0001
0.0228
0.0111
<.0001
0.0002
0.0005
Based on the regression results from the first decade of the 21st century, it appears that
right-to-work laws had no effect on population growth during this time period. This regression
model explained approximately 50% of the variation in the dependent variable, population
growth from 2000 to 2010. This model is represented in Chart 9 on the next page. Southern
states experienced GDP growth of almost 8% more on average than their northern counterparts
during this time period. For every 1% increase in GDP from 2000 to 2010, states experienced
.15% greater population growth on average (SE = .06). Average unemployment also had a
positive effect on population growth, again attributable to frictional unemployment. This
parameter coefficient was estimated to be 2.5 with a standard error of 1.01. The average labor
17
force participation rate was significant, with a coefficient of .866 and standard error of .282.
Using this model, and excluding all insignificant parameters, Arkansas would be projected to
growth 17.8% in population from 2000 to 2010. Since Arkansas’s population actually grew by
9.1% during that time, one must conclude that Arkansas’s residents fared very well, receiving the
economic benefits of a 50.5% increase in GDP and a 34% increase in average wages during the
time period. However, the researcher cannot attribute these growths to Arkansas’s right-to-work
legislation.
Chart 9: Regression Analysis Population Growth 2000-2010
(Dependent Variable: Pop. Growth)
Analysis of Variance
Source
Model
Error
Corrected Total
DF
6
43
49
Sum of
Squares
1292.8
1308.053
2600.854
5.51542
9.782
Root MSE
Dependent
Mean
Coeff Var
56.38335
Parameter Estimates
Variable
Intercept
RTW (1) 00-10
South 25
Increase in GDP 00-11
AVG Unemployment 00-10
AVG LFPR 00-10
% Increase In HRLY Wage (2000s)
DF
1
1
1
1
1
1
1
Parameter
Estimate
-62.6145
2.33686
7.97488
0.15053
2.50131
0.86623
-0.27289
Mean
Square
215.4667
30.41985
R-Square
Adj R-Sq
Standard
Error
22.7739
1.95905
1.96326
0.063
1.00603
0.28216
0.21225
F Value
7.08
Pr > F
<.0001
0.4971
0.4269
t Value
-2.75
1.19
4.06
2.39
2.49
3.07
-1.29
Pr > |t|
0.0087
0.2395
0.0002
0.0213
0.0169
0.0037
0.2054
While the increase in GDP did have a significant effect on the population growth, the
increase in hourly wages was not a significant driver of population increases. This would seem to
indicate that the increase in GDP that created jobs gave a boost to population growth, but those
newly created jobs were more of an attractive factor for states than increases in wages. This
could be explained by the fact that right-to-work states and non-right-to-work states experienced
percentage increases in hourly wages that were statistically the same. Wages (across all
industries) in right-to-work states increased by 33.28% from 2000 to 2010. Similarly, wages in
non-right-to-work states grew by 33.26% during that time period. This was not a statistically
significant difference. Arkansas outperformed both averages, with wages increasing by 34.8%
during this decade. Since wages grew at roughly the same pace between right-to-work states and
their counterparts, it makes sense that the majority of population gains in states were motivated
by job creation. Job creation in turn, was driven by increases in GDP (output) in the right-towork states. From 2000 to 2010, GDP grew by an average of 59.6% in right-to-work states
versus a 47.72% increase in GDP in non-right-to-work states. This difference was significant at
the 98% confidence level. Arkansas fared pretty well, with its GDP increasing by 50.5% during
this time span. Arkansas experienced a greater increase in GDP than the average state without
18
right-to-work laws, but as was the pattern, it fell short of the average performance of the
aggregate of right-to-work states. Based on this, right-to-work appears to have positively affected
Arkansas’s GDP growth in the first decade of the new millennium.
Conclusion
When looking at the results drawn from the data, there is insufficient evidence to declare
unequivocally that right-to-work has been good for Arkansas. While right-to-work states have
been shown to have unemployment rates, labor force participation rates, and average wage
growth rates that are statistically the same as non-right-to-work states, Arkansas has consistently
underperformed in these categories. On the other hand, right-to-work states have experienced
statistically higher population growth and higher GDP growth during the past few decades than
their right-to-work counterparts. Regression analysis indicates that right-to-work has been
partially responsible for these discrepancies, and Arkansas has consistently outperformed the
non-right-to-work state averages during recent years.
Based on a review of the data analysis employed during the course of this research, and a
thorough analysis of the corresponding literature based on past studies, it is a conclusion of the
researcher that right to work laws are more pro economic growth than their non-right-to-work
counterparts, particularly in the short term. Unfortunately, the state of Arkansas's economy has
not been privy to all of the improvements in economic stability with which many of the other
right-to-work states have been blessed. However, this is not to say that Arkansas should repeal
its right-to-work laws. All of the economic growth that Arkansas has experienced during the
greater part of the last century has been done with right-to-work laws in effect. Currently,
Arkansas enjoys lower unemployment, a higher population growth rate, and a higher GDP
growth rate over the past ten years than non-right-to-work states do on average. The economy of
Arkansas is not perfect by any stretch of the imagination, but it is performing adequately, and
when considering the current condition of our nation’s economy, that’s certainly a positive.
19
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